FRACTAL GEOMETRY-BASED RESOURCE ALLOCATION FOR MIMO RADAR
Hui Li,
Ao Lou,
Borong Zou,
Yuanyang Cheng and
Kang-Jia Wang
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Hui Li: School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, P. R. China
Ao Lou: School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, P. R. China
Borong Zou: School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, P. R. China
Yuanyang Cheng: School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, P. R. China
Kang-Jia Wang: School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, P. R. China
FRACTALS (fractals), 2024, vol. 32, issue 07n08, 1-11
Abstract:
The netted Collocated Multiple-Input Multiple-Output (C-MIMO) radar systems have attracted widespread attention due to their high resolution and excellent target detection capabilities. The self-similarity and spatial filling properties of fractal geometry enable antenna layouts to function effectively across multiple scales and frequency bands, which helps improve the overall performance and resource utilization of systems. In this paper, a radar array element model based on the Fudgeflake fractal is used to establish a target localization performance model directly related to power bandwidth allocation. Based on the model, a three-step solving strategy was designed with the Sequence Quadratic Program (SQP) algorithm as the foundation to achieve optimized allocation of power and bandwidth while maximizing overall performance. Experimental results demonstrate that under this algorithm, the use of power bandwidth resources is optimized through fractal geometry-based design.
Keywords: Collocated MIMO Radar; Fractal Geometry; Resource Allocation; Power Optimization; Sparrow Search Algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0218348X24400474
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